MATLAB Simulation of Complex Networks

This paper provides a comprehensive introduction and analysis of MATLAB-based complex network simulations. Specifically, we explore the characteristics and statistical features of AB (Arena-Barabási) and BA (Barabási-Albert) scale-free network models, along with WS (Watts-Strogatz) and NW (Newman-Watts) small-world network models, conducting comparative analysis between them. The implementation involves MATLAB's graph theory toolbox functions like graph, WattsStrogatz, and preferential attachment algorithms for BA model generation. We examine key network metrics including degree distribution, clustering coefficient, and average path length calculations using functions like degree, clustering_coeff, and distances. Additionally, we discuss practical applications of these models across various domains and demonstrate their implementation for real-world problem solving. Finally, we explore future research directions and potential improvements to enhance these models' adaptability for broader application scenarios. Statistical analysis includes MATLAB-based computation of network properties and visualization using plot functions for comparative model evaluation.